The most robust data for vax effectiveness waning is from randomised control trials. Pfizer👇
2doses holds up well- but still complete the course and boost!
This is real world data. Prospective randomisation only reduces confounding we face in retrospective observations.
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Sources of bias/confounding in observational data (eg UKHSA case control study below):
▪️ accrued natural immunity in control (>45% 🏴 infected) & only a fraction tested
▪️ difficulty of retrospective matching/case controlling (high clinical risk vaxxed first, not just age)
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▪️ break throughs disproportionately sample higher risk (immunocompromised, preexisting conditions, etc)
▪️ lower test seeking behaviour in unvaxxed
▪️ pop highest risk of infection (urban, young, ethic minority, high deprivation) also lower vax uptake
Grateful for the hard work of dedicated public health scientists at @PHE_uk like @kallmemeg and unsung others who work overtime to produce excellent reports on the variant of concern B1.617.2 🇮🇳
🧵analysis of vax effectiveness, and why interpretation of reduced VE limited.
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PHE did a 'test negative case control study' w/ logistic regression as I outlined yday.
From test and vax databases they retrospectively created a control cohort of 99k who tested negative and compared to 6.4k test positive for B117 & 1k for B1.617.2
The longer it takes to statistically tell difference between vax effectiveness against variants the smaller the actual dip (if any) in protection will be.
In randomised control trials we can be confident in vax effect after only 100+ infections because selection bias and confounding variables between the vaxxed and unvaxxed comparison populations are (e)limited by the randomisation process.
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This is not the case when we do retrospective observational studies - like vax effectiveness against variants in the field.
The statistical analysis is more challenging. There are biases in who is vaxxed or infected, living, working, mixing patterns, medical health/immunity.
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